A recently developed computer program was designed to assist drug developers and other life science researchers that work with kinase microarrays to evaluate the kinomic data that they obtain.

The kinome of an organism is the set of protein kinases in its genome. Kinases are enzymes that catalyze phosphorylation reactions (of amino acids) and fall into several groups and families, e.g., those that phosphorylate the amino acids serine and threonine, those that phosphorylate tyrosine, and some that can phosphorylate both, such as the MAP2K and GSK families. As kinases are a major drug target and a major control point in cell behavior, the kinome has also been the target of large-scale functional genomics with siRNA screens and of drug discovery efforts, especially in cancer therapeutics.

Up to now, the computational tools used to perform high-throughput kinome analyses were not specifically tailored to the nature of the data, which hindered extraction of biological information and overall progress in the field. To correct this situation investigators at the University of Saskatchewan, Saskatoon, Canada) designed a computer program that evaluated data produced by kinase microarrays, a different type of data than that obtained from the more common DNA or RNA type of microarray.

They reported in the April 17, 2012, online edition of the journal Science Signaling that they had performed comparative analysis of kinome data sets that corresponded to stimulation of immune cells with ligands of well-defined signaling pathways: bovine monocytes treated with interferon-gamma, CpG-containing nucleotides, or lipopolysaccharide (LPS). The data sets for each of the treatments were analyzed with the new software as well as with three other commonly used approaches. Results showed that the new approach identified more of the peptides involved in the pathways than did the other compared methods and that it did so at a much higher degree of statistical confidence.

“This is a premiere example of what can be achieved through interdisciplinary and collaborative research," said senior author Dr. Tony Kusalik, professor of computer science at the University of Saskatchewan. “By developing a technique specifically designed for kinase microarrays we are able to get more data, and with more accuracy.”

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